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An Automated Algorithm for Decline Analysis

By Randall Pyke

Abstract

Oil and gas wells are regularly monitored for their production rates. For a variety of reasons, typical production rate data is noisy and highly discontinuous, and we wish to use this data to extrapolate trends in the production rate to forecast future production and ultimate cumulative reserve recovery. The proposed solution consists of three main steps: (1) Segmentation of Data, (2) Curve fitting, and (3) a Decision Process. Segmentation of Data attempts to identify intervals in the data where a single trend is dominant. A curve from an appropriate family of functions is then fitted to this interval of data. The Decision Process gauges the quality of the trends identified and either formulates a final answer or, if the program cannot come to a reliable answer, ' flags' the well to be looked at by an operator

Topics: Energy and utilities
Year: 2001
OAI identifier: oai:generic.eprints.org:170/core70

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Citations

  1. (1997). Neural Network Models,
  2. (1992). Ten Lectures on Wavelets, doi

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